In order to exploit the angular dependencies between LF views, the views should be arranged in the form of a pseudo-video sequence to feed an LSTM network. In [1]}, 11 different sampling schemes were considered to select and scan the set of SA images, notably varying their number, position, and scanning order. The results showed that capturing angular information along the horizontal and vertical directions leads to better average performance when compared to other sampling schemes, notably due to the consideration of larger disparities. The results also showed that the score-level fusion of horizontal and vertical angular classification models leads to additional improvements.
